Efficient noise-tolerant learning from statistical queries
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
Efficient clustering of high-dimensional data sets with application to reference matching
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Confidence estimation for machine translation
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Identifying and analyzing judgment opinions
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Paraphrasing for automatic evaluation
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
SenseRelate::TargetWord: a generalized framework for word sense disambiguation
ACLdemo '05 Proceedings of the ACL 2005 on Interactive poster and demonstration sessions
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
The rendezvous algorithm: multiclass semi-supervised learning with Markov random walks
Proceedings of the 24th international conference on Machine learning
Fully distributed EM for very large datasets
Proceedings of the 25th international conference on Machine learning
Proceedings of the 19th international conference on World wide web
Experiments in graph-based semi-supervised learning methods for class-instance acquisition
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Ranking on large-scale graphs with rich metadata
Proceedings of the 20th international conference companion on World wide web
Multi-layer graph-based semi-supervised learning for large-scale image datasets using mapreduce
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Semi-supervised ranking on very large graphs with rich metadata
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Harvesting facts from textual web sources by constrained label propagation
Proceedings of the 20th ACM international conference on Information and knowledge management
Large-scale graph mining and learning for information retrieval
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Robust re-identification using randomness and statistical learning: Quo vadis
Pattern Recognition Letters
Multimedia Applications and Security in MapReduce: Opportunities and Challenges
Concurrency and Computation: Practice & Experience
Graph-based semi-supervised learning with multi-modality propagation for large-scale image datasets
Journal of Visual Communication and Image Representation
Relational large scale multi-label classification method for video categorization
Multimedia Tools and Applications
Hi-index | 0.00 |
Label Propagation, a standard algorithm for semi-supervised classification, suffers from scalability issues involving memory and computation when used with large-scale graphs from real-world datasets. In this paper we approach Label Propagation as solution to a system of linear equations which can be implemented as a scalable parallel algorithm using the map-reduce framework. In addition to semi-supervised classification, this approach to Label Propagation allows us to adapt the algorithm to make it usable for ranking on graphs and derive the theoretical connection between Label Propagation and PageRank. We provide empirical evidence to that effect using two natural language tasks -- lexical relat-edness and polarity induction. The version of the Label Propagation algorithm presented here scales linearly in the size of the data with a constant main memory requirement, in contrast to the quadratic cost of both in traditional approaches.